Title:Estimating and Forecasting the Smoking-Attributable Mortality Fraction for Both Sexes Jointly in 69 Countries

Abstract: Smoking is one of the preventable threats to human health and is a major risk
factor for lung cancer, upper aero-digestive cancer, and chronic obstructive
pulmonary disease. Estimating and forecasting the smoking attributable fraction
(SAF) of mortality can yield insights into smoking epidemics and also provide a
basis for more accurate mortality and life expectancy projection. Peto et al.
(1992) proposed a method to estimate the SAF using the lung cancer mortality
rate as an indicator of exposure to smoking in the population of interest. Here
we use the same method to estimate the all-age SAF (ASAF) for both sexes for 69
countries. We document a strong and cross-nationally consistent pattern of the
evolution of the SAF over time. We use this as the basis for a new Bayesian
hierarchical model to project future male and female ASAF from 69 countries
simultaneously. This gives forecasts as well as predictive distributions that
can be used to find uncertainty intervals for any quantities of interest. We
assess the model using out-of-sample predictive validation, and find that it
provides good forecasts and well calibrated forecast intervals.